001     1041740
005     20250507203500.0
024 7 _ |a 10.34734/FZJ-2025-02416
|2 datacite_doi
037 _ _ |a FZJ-2025-02416
041 _ _ |a English
100 1 _ |a Baumann, Thomas
|0 P:(DE-Juel1)190575
|b 0
|e Corresponding author
|u fzj
111 2 _ |a Numerical algorithms seminar at University of Exeter
|c Exeter
|w UK
245 _ _ |a Spectral Deferred Correction
|f 2025-01-30 -
260 _ _ |c 2025
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a Other
|2 DataCite
336 7 _ |a INPROCEEDINGS
|2 BibTeX
336 7 _ |a LECTURE_SPEECH
|2 ORCID
336 7 _ |a Talk (non-conference)
|b talk
|m talk
|0 PUB:(DE-HGF)31
|s 1746606389_7883
|2 PUB:(DE-HGF)
|x Invited
336 7 _ |a Other
|2 DINI
520 _ _ |a Spectral deferred correction (SDC) is a time integration method that is closely related to Runge-Kutta methods (RKM). In SDC, fully implicit RKM are solved iteratively, using similar computations as required to compute the stages in RKM. While explicit SDC often cannot compete with explicit RKM, SDC has been shown to perform very well for stiff PDEs. One major advantage of SDC is the flexibility afforded by using a low-order solver inside an iterative method for obtaining high-order solutions. This makes it simple to construct high-order splitting methods, for instance. SDC is also popular in the parallel-in-time community. Efficient small-scale parallelism within the method has recently been achieved and SDC is also employed within various parallel-in-time algorithms. This talk will encompass an introduction to SDC, some recent developments, numerical experiments where time-parallel SDC is preferable to RKM, and an advertisement for the prototyping library pySDC, which allows to rapidly explore all things SDC.
536 _ _ |a 5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5112
|c POF4-511
|f POF IV
|x 0
536 _ _ |a TIME-X - TIME parallelisation: for eXascale computing and beyond (955701)
|0 G:(EU-Grant)955701
|c 955701
|f H2020-JTI-EuroHPC-2019-1
|x 1
856 4 _ |u https://juser.fz-juelich.de/record/1041740/files/SDC.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:1041740
|p openaire
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910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)190575
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5112
|x 0
914 1 _ |y 2025
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 0
980 1 _ |a FullTexts
980 _ _ |a talk
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)JSC-20090406


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